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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Interpretable machine learning for psychological research: Opportunities and pitfalls.
Mirka Henninger, Rudolf Debelak, Yannick Rothacher, et al.
Psychological Methods (2023)
Open Access | Times Cited: 30

Showing 1-25 of 30 citing articles:

Machine learning in international business
Bas Bosma, A. van Witteloostuijn
Journal of International Business Studies (2024) Vol. 55, Iss. 6, pp. 676-702
Closed Access | Times Cited: 11
Detecting noncredible symptomology in ADHD evaluations using machine learning
John-Christopher A. Finley, Matthew S. Phillips, Jason R. Soble, et al.
Journal of Clinical and Experimental Neuropsychology (2025), pp. 1-11
Closed Access | Times Cited: 1
Predicting Mood Based on the Social Context Measured Through the Experience Sampling Method, Digital Phenotyping, and Social Networks
Anna M. Langener, Laura F. Bringmann, Martien J. Kas, et al.
Administration and Policy in Mental Health and Mental Health Services Research (2024) Vol. 51, Iss. 4, pp. 455-475
Open Access | Times Cited: 6
Identifying Informative Predictor Variables With Random Forests
Yannick Rothacher, Carolin Strobl
Journal of Educational and Behavioral Statistics (2023) Vol. 49, Iss. 4, pp. 595-629
Open Access | Times Cited: 15
Partial credit trees meet the partial gamma coefficient for quantifying DIF and DSF in polytomous items
Mirka Henninger, Jan Radek, Marie‐Ann Sengewald, et al.
Behaviormetrika (2025)
Open Access
Cross-validation and predictive metrics in psychological research: Do not leave out the leave-one-out
Diego Iglesias, Miguel A. Sorrel, Ricardo Olmos
Behavior Research Methods (2025) Vol. 57, Iss. 3
Closed Access
Shedding Light on the Black Box: Integrating Prediction Models and Explainability Using Explainable Machine Learning
Yucheng Zhang, Yuyan Zheng, Dan Wang, et al.
Organizational Research Methods (2025)
Closed Access
Decoding vital variables in predicting different phases of suicide among young adults with childhood sexual abuse: a machine learning approach
Wenbang Niu, Yi Feng, Jiaqi Li, et al.
Translational Psychiatry (2025) Vol. 15, Iss. 1
Open Access
How can we build structural resilience? Integration of social-ecological and minority stress models.
Sharon Y. Lee, Chrystal Vergara‐Lopez, Ernestine Jennings, et al.
American Psychologist (2024) Vol. 79, Iss. 8, pp. 1012-1024
Closed Access | Times Cited: 3
From Embeddings to Explainability: A Tutorial on Transformer-Based Text Analysis for Social and Behavioral Scientists
Rudolf Debelak, Timo Kevin Koch, Matthias Aßenmacher, et al.
(2024)
Open Access | Times Cited: 2
Partial credit trees meet the partial gamma coefficient for quantifying DIF and DSF in polytomous items
Mirka Henninger, Jan Radek, Marie‐Ann Sengewald, et al.
(2024)
Open Access | Times Cited: 1
The Association Between Mindfulness, Psychological Flexibility, and Rumination in Predicting Mental Health and Well-Being Among University Students Using Machine Learning and Structural Equation Modeling
Ruohan Feng, Vaibhav Mishra, Hao Xin, et al.
Machine Learning with Applications (2024), pp. 100614-100614
Open Access | Times Cited: 1
Interpreting machine learning predictions with LIME and Shapley values: theoretical insights, challenges, and meaningful interpretations
Mirka Henninger, Carolin Strobl
Behaviormetrika (2024)
Closed Access | Times Cited: 1
Interpretable machine learning for psychological research: Opportunities and pitfalls
Mirka Henninger, Rudolf Debelak, Yannick Rothacher, et al.
(2022)
Open Access | Times Cited: 5
Local interpretation techniques for machine learning methods: Theoretical background, pitfalls and interpretation of LIME and Shapley values
Mirka Henninger, Carolin Strobl
(2023)
Open Access | Times Cited: 2
Responsible research assessment in the area of quantitative methods research: A comment on Gärtner et al.
Holger Brandt, Mirka Henninger, Esther Ulitzsch, et al.
Meta-Psychology (2024) Vol. 8
Open Access
Decoding Vital Variables in Predicting Different Phases of Suicide Among Young Adults with Childhood Sexual Abuse: A Machine Learning Approach
W D Niu, Yi Feng, Jiaqi Li, et al.
(2024)
Closed Access
fabOF: A Novel Tree Ensemble Method for Ordinal Prediction
Philip Buczak
(2024)
Open Access
Detecting Workplace Hubris: A Machine Learning Approach to Narcissism Identification. The Case of the Healthcare Industry in the Emerging Markets
Rachid Alami
(2024)
Closed Access
Interaction Difference Hypothesis Test for Prediction Models
Thomas Welchowski, Dominic Edelmann
Machine Learning and Knowledge Extraction (2024) Vol. 6, Iss. 2, pp. 1298-1322
Open Access
<p><b><span>Revisiting the Nature and Strength of the Personality-Job Performance Relations:&nbsp;</span></b><b><span>New Insights from Interpretable Machine Learning</span></b></p>
Q. Chelsea Song, In‐Sue Oh, Yesuel Kim, et al.
(2024)
Closed Access
From Data Streams to Mental Health Predictions: Improving the use of Passive Measures from Digital Devices
Anna Langener
(2024)
Open Access
The iterative development and refinement of health psychology theories through formal, dynamical systems modelling: a scoping review and initial expert-derived ‘best practice’ recommendations
Olga Perski, Amber Copeland, Jim Allen, et al.
Health Psychology Review (2024), pp. 1-44
Open Access
Detecting interactions with random forests: a comment on Gries’ words of caution and suggestions for improvement
Carolin Strobl, Yannick Rothacher, Sven Theiler, et al.
Corpus Linguistics and Linguistic Theory (2024)
Closed Access
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